Deep learning (DL) models have achieved state-of-the-art performance in many visual recognition applications such as image classification [1]}, object detection [2]}, and segmentation [3]}, [4]}. However, large annotated datasets are required for supervised training of these models [5]}.
In computer vision, the weakly supervised learning (WSL) paradigm has received considerable attention in object localization, allowing to avoid a costly bounding-box or pixel-label annotation process to train a DL model [6]}. In particular, weakly supervised object localization (WSOL) involves locating an object of interest in an image based on training data with only images-class labels.
<FIGURE>